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https://github.com/logos-blockchain/logos-blockchain-simulations.git
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Targeted experiments for queuing mechanism gather series into dataframe put exp_id to the CSV path revert iterations back to num_nodes/2 add missing print and decrease msg_interval_sec change param sequence for readability use struct instead of pickle for fixed-size & faster serde include dtime series into dataframe optimize: choose optimized connection type according to latency setting add skip_sending_noise option optimize filling up the queue with noises move queue_type to the end of param set, and build CSV gradually row by row fix: consider num_senders when waiting until all messages are disseminated fix: sample senders without duplicate fix: build param combinations correctly add plot script initialize MinSizeMixQueue with noises define SessionParameterSet and add paramset for session2 improve topology connectivity check to avoid "maxmimum recursions depth exceeded" error fix: the correct parameter set constructor store individual series to separate CSV files reorganize files and draw plot automatically start series file id from 1 (not 0) add queue_type CLI argument for parallelization pretty format of elapsed time pretty format of elapsed time add merge CLI and draw multiple plots split functions do not draw plot for each session use concurrent.futures to utilize multiprocessing add from_paramset argument fix: count num of finished iterations correctly draw plots for num_sent_msgs and num_senders for specific experiments
54 lines
2.1 KiB
YAML
54 lines
2.1 KiB
YAML
simulation:
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# Desired duration of the simulation in seconds
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# Since the simulation uses discrete time steps, the actual duration may be longer or shorter.
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duration_sec: 1000
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# Show all plots that have been drawn during the simulation
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show_plots: false
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network:
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# Total number of nodes in the entire network.
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num_nodes: 6
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latency:
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# Minimum/maximum network latency between nodes in seconds.
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# A constant latency will be chosen randomly for each connection within the range [min_latency_sec, max_latency_sec].
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min_latency_sec: 0
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max_latency_sec: 0.1
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# Seed for the random number generator used to determine the network latencies.
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seed: 0
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gossip:
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# Expected number of peers each node must connect to if there are enough peers available in the network.
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peering_degree: 3
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topology:
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# Seed for the random number generator used to determine the network topology.
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seed: 1
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mix:
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# Global constant transmission rate of each connection in messages per second.
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transmission_rate_per_sec: 10
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# Maximum size of a message in bytes that can be encapsulated in a single Sphinx packet.
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max_message_size: 1007
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mix_path:
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# Minimum number of mix nodes to be chosen for a Sphinx packet.
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min_length: 5
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# Maximum number of mix nodes to be chosen for a Sphinx packet.
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max_length: 5
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# Seed for the random number generator used to determine the mix path.
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seed: 3
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temporal_mix:
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# none | pure-coin-flipping | pure-random-sampling | permuted-coin-flipping
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mix_type: "pure-coin-flipping"
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# The minimum size of queue to be mixed.
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# If the queue size is less than this value, noise messages are added.
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min_queue_size: 5
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# Generate the seeds used to create the RNG for each queue that will be created.
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seed_generator: 100
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logic:
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sender_lottery:
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# Interval between lottery draws in seconds.
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interval_sec: 1
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# Probability of a node being selected as a sender in each lottery draw.
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probability: 0.001
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# Seed for the random number generator used to determine the lottery winners.
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seed: 10
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